These data come from the 2016 CCES and allow interested students to model the individual correlates of the Trump vote in 2016. Code/analysis heavily indebted to a 2017 analysis I did on my blog (see references).
Format
A data frame with 64600 observations on the following 21 variables.
uida numeric vector, a unique identifier for the respondent as they first appear in the CCES data.
statea character vector for the state in which the respondent resides
votetrumpa numeric that equals 1 if the respondent voted says s/he voted for Trump in 2016.
agea numeric vector for age that is roughly calculated as 2016 -
birthyr, as it's coded in the CCES data.femalea numeric that equals 1 if the respondent is a woman
collegeeda numeric vector that equals 1 if the respondent says s/he has a college degree
racefa character vector for the race of the respondent
famincra numeric vector for the respondent's household income. Ranges from 1 (Less than $10,000) to 12 ($150,000 or more).
ideoa numeric vector for the respondent's ideology on a liberal-conservative discrete scale. 1 = very liberal. 5 = very conservative.
pid7naa numeric vector for the respondent's partisanship on the familiar 1-7 scale. 1 = Strong Democrat. 7 = Strong Republican. Other party supporters (e.g. libertarians) are coded as NA.
bornagaina numeric vector for whether the respondent self-identifies as a born-again Christian.
religimpa numeric vector for the importance of religion to the respondent. 1 = not at all important. 4 = very important.
churchatda numeric vector for the extent of church attendance for the respondent. 1 = never. 6 = more than once a week.
prayerfreqa numeric vector for the frequency of prayer for the respondent. 1 = never. 7 = several times a day.
angryracisma numeric vector for how angry the respondent is that racism exists. 1 = strongly agree (i.e. is angry racism exists). 5 = strongly disagree.
whiteadva numeric vector for agreement with statement that white people have advantages over others in the U.S. 1 = strongly agree. 5 = strongly disagree.
fearracesa numeric vector for agreement with statement that the respondent fears other races. 1 = strongly disagree. 5 = strongly agree.
racerarea numeric vector for agreement with statement that racism is rare in the U.S. 1 = strongly disagree. 5 = strongly agree.
lreliga numeric vector that serves as a latent estimate for religiosity from the
bornagain,religimp,churchatd, andprayerfreqvariables. Higher values = more religiosity.lcograca numeric vector that serves as a latent estimate for cognitive racism. This is derived from the
racerareandwhiteadvvariables.lempraca numeric vector that serves as a latent estimate for empathetic racism. This is derived from the
fearracesandangryracismvariables.